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Record W3035054228 · doi:10.3997/2214-4609.201950156

Geochemical Characteristics of Sapropelite in the Bazhenov Formation Deposits

2019· article· en· W3035054228 on OpenAlexaff
Timur Bulatov, Елена Козлова, Mikhail Spasennykh, Е. Leushina

Bibliographic record

VenueGeomodel 2019 · 2019
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsOptech (Canada)
Fundersnot available
KeywordsQuartzGeologyOrganic matterGeochemistryPetrographyPyrolysisLithologyMineralogySource rockPetroleumStructural basinChemistryGeomorphologyPaleontology

Abstract

fetched live from OpenAlex

Summary Due to increasing interest to oil shales, study of the Bazhenov Formation deposits of the West Siberian Petroleum Basin is progressing extensively. Despite the seeming homogeneity, in closer observation the composition of the Bazhenov Formation rocks vary significantly. The main objectives were to characteristic lithology and geochemistry of the Bazhenov Formation rocks containing sapropelite interlayers. The material for the present study were core samples from several wells located in the central part of the West Siberian Petroleum Basin. During this research, samples were selected, petrographic thin sections were made and described, and pyrolysis and kinetic studies were carried out by the HAWK pyrolysis from Wildcat Technology. The current study reveals, sapropelite interlayers are characterized by high content of alginitic organic matter. The origin is yet unknown but two possible ways of forming of such deposits were proposed. The Bazhenov Formation sapropelite consist of 30÷35 % alginate with quartz and chalcedonic inclusions. Pyrolysis characteristics of sapropelite interlayers differ from host deposits by anomalously high hydrogen index HI (up to 1015 mg HC/g TOC). According to bulk-kinetics study, the whole organic matter of sapropelites transforms to HCs at single Ea around 53 kcal/mol.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.190
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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